School of Engineering
Showing 1,051-1,100 of 1,923 Results
-
Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
BioChristopher Manning is the inaugural Thomas M. Siebel Professor in Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing, work for which he won ACL, Coling, EMNLP, and CHI Best Paper Awards. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. In linguistics, Manning is a principal developer of Stanford Dependencies and Universal Dependencies, and has authored monographs on ergativity and complex predicates. He is the founder of the Stanford NLP group (@stanfordnlp) and was an early proponent of open source software in NLP with Stanford CoreNLP and Stanza. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023. He held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford.
-
Blake Masters
Graduate, Computer Science
BioDesign and implementation of artificial intelligence systems.
-
David Mazieres
Professor of Computer Science
BioMazieres investigates ways to improve the security of operating systems, file systems, and distributed systems. In addition, he has worked on large-scale peer-to-peer systems and e-mail privacy.
-
Jay McClelland
Lucie Stern Professor in the Social Sciences, Professor of Psychology and, by courtesy, of Linguistics and of Computer Science
Current Research and Scholarly InterestsMy research addresses topics in perception and decision making; learning and memory; language and reading; semantic cognition; and cognitive development. I view cognition as emerging from distributed processing activity of neural populations, with learning occurring through the adaptation of connections among neurons. A new focus of research in the laboratory is mathematical cognition and reasoning in humans and contemporary AI systems based on neural networks.
-
Brando Miranda
Ph.D. Student in Computer Science, admitted Autumn 2022
BioBio
Brando Miranda is a current Ph.D. Student at Stanford University under the supervision of Professor Sanmi Koyejo in the department of Computer Science. Previously he has been a graduate student at University of Illinois Urbana-Champaign, Research Assistant at MIT’s Center for Brain Minds and Machines (CBMM), and graduate student at the Massachusetts Institute of Technology (MIT). Miranda’s research interests lie in the field of meta-learning, foundation models for theorem proving, and human & brain inspired Artificial Intelligence (AI). Miranda completed his Master of Engineering in Electrical Engineering and Computer Science under the supervision of Professor Tomaso Poggio – where he did research on Deep Learning Theory. Miranda has been the recipient of several awards, including Most Cited Paper Certificate awarded by International Journal of Automation & Computing (IJAC), two Honorable Mention with the Ford Foundation Fellowship, Computer Science Excellence Saburo Muroga Endowed Fellow, Stanford School of Engineering fellowship, and is currently an EDGE Scholar at Stanford University.
About me (Informal)
I am a scientist and an engineer that is interested in moving forward the powerful and beautiful field of A.I. closer to true Artificial General Intelligence (AGI). I believe an important direction is understanding how to combine cognitive and neuro-inspired models, specially investigating how reasoning and learning work together. In addition, I also believe being able to adapt to new tasks using prior experience and knowledge is crucial for AGI to occur. Consequently, I decided to pursue a Ph.D in AI and machine learning. I currently work on meta-learning and machine learning (ML) for Theorem Proving (TP) at Stanford University.
